#import
import tensorflow as tf
import keras
import tensorflow.keras.layers as KL

## Dataset
mnist = keras.datasets.mnist
(x_train, y_train), (x_test, y_test) = mnist.load_data()
x_train, x_test = x_train/255.0, x_test/255.0

## Model
inputs = KL.Input(Shape=(28, 28))
x = KL.SimpleRNN(64,activation='relu')(inputs)
outputs = KL.Dense(10,activation='softmax')(x)

model = keras.models.Model(inputs, outputs)
model.summary()

model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metics=['acc'])

model.fit(x_train, y_train, epochs=5)
test_loss, test_acc = model.evaluate(x_test, y_test)
print("Loss: {0} - Acc: {1}".format(test_loss, test_acc))